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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

A Boiling-Potassium Fluoride Reactor for an Artificial-Gravity NEP Vehicle

Several years ago a rotating manned spacecraft employing nuclear-electric propulsion was examined for Mars exploration. The reactor and its power conversion system essentially served as the counter-mass to an inflatable manned module. A solid-core boiling potassium reactor based on the MPRE concept of the 1960s was baselined in that study. This paper proposes the use of a liquid-fluoride reactor, employing direct boiling of potassium in the core, as a means to overcome some of the residual issues with the MPRE reactor concept. Several other improvements to the rotating Mars vehicle are proposed as well, such as Canfield joints to enable the electric engines to track the inertial thrust vector during rotation, and innovative "cold-ion" engine technologies to improve engine performance.

Sorensen, Kirk↗
DOE OSTI2023

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore’s Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to MLexperts because of lack of training data and relevant, easy-to-use workflows. Wepresent ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state. The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res2) and code(https://leap-stc.github.io/ClimSim)arereleasedopenlytosupport the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society.

artificial intelligence, machine learning↗
DOE OSTI2024

Cy-Phy ADS: Cyber Physical Anomaly Detection Framework for EV Charging Systems

Today’s large-scale Electric Vehicle (EV) infrastructures are heavily dependent on information communication technologies to maintain their operation and to support communication within sub-system components as well as the outside world. These technologies are vulnerable to various cyber and physical threats. Timely identification and mitigation of these threats are critical for improving human safety, avoiding economic losses, and preventing catastrophic system failures. By addressing this, our work presents a ResNet Autoencoder (AE) based Cyber-Physical Anomaly Detection System (Cy-Phy ADS) for detecting anomalies in EV Controller Area Network (CAN) protocol communication. It consists of four main components: Cyber-Physical Feature Extractor, ResNet AE-based Anomaly Detection Framework, Cyber-Physical Health Metric (CPHM), and Visualization Dashboard. The presented framework was trained and tested using CAN data collected from the EV charging system testbed at the Idaho National Laboratory. The presented Cy-Phy ADS compared against six widely used unsupervised anomaly detection algorithms: One Class Support Vector Machine (OCSVM), Variational Autoencoder (VAE), LSTM Autoencoder (LSTM AE), Isolation Forest (IForest), Principle Component Analysis (PCA) and Local Outlier Factor (LOF). Here the presented approach showed the highest accuracy among the compared methods. Further, the proposed approach showed comparable performance in terms of precision, F1, and False positive rate. It also showed the lowest training and inference time compared to the neural network-based baseline algorithms compared against with. Additionally, the Cy-Phy ADS has advantages such as unsupervised training, the ability to provide a holistic metric for system health characterization, and non-linear feature extraction.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Anisotropic Flow in Fixed-Target 208 Pb + 20 Ne Collisions as a Probe of Quark-Gluon Plasma

The System for Measuring Overlap with Gas (SMOG2) at the LHCb detector enables the study of fixed-target ion-ion collisions at relativistic energies ($\sqrt{𝑠_{NN}}$ ∼ 100 GeV in the center of mass). Here, with input from ab initio calculations of the structure of 16 O and 20 Ne , we compute 3+1⁢D hydrodynamic predictions for the anisotropic flow of Pb+Ne and Pb+O collisions to be tested with upcoming LHCb data. This will allow the detailed study of quark-gluon plasma formation as well as experimental tests of the predicted nuclear shapes. Elliptic flow (𝑣 2 ) in Pb + Ne collisions is greatly enhanced compared to the Pb + O baseline due to the shape of 20 Ne , which is deformed in a bowling-pin geometry. Owing to the large 208 Pb radius, this effect is seen in a broad centrality range, a unique feature of this collision configuration. Larger elliptic flow further enhances the quadrangular flow (𝑣 4 ) of Pb + Ne collisions via nonlinear coupling, and impacts the sign of the kurtosis of the elliptic flow vector distribution (𝑐 2 ⁡{4}). Exploiting the shape of 20 Ne proves thus an ideal method to investigate the formation of quark-gluon plasma in fixed-target experiments at LHCb, and demonstrates the power of System for Measuring Overlap with Gas as a tool to image nuclear ground states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2005

The Optimization of Trained and Untrained Image Classification Algorithms for Use on Large Spatial Datasets

The HARVIST project seeks to automatically provide an accurate, interactive interface to predict crop yield over the entire United States. In order to accomplish this goal, large images must be quickly and automatically classified by crop type. Current trained and untrained classification algorithms, while accurate, are highly inefficient when operating on large datasets. This project sought to develop new variants of two standard trained and untrained classification algorithms that are optimized to take advantage of the spatial nature of image data. The first algorithm, harvist-cluster, utilizes divide-and-conquer techniques to precluster an image in the hopes of increasing overall clustering speed. The second algorithm, harvistSVM, utilizes support vector machines (SVMs), a type of trained classifier. It seeks to increase classification speed by applying a "meta-SVM" to a quick (but inaccurate) SVM to approximate a slower, yet more accurate, SVM. Speedups were achieved by tuning the algorithm to quickly identify when the quick SVM was incorrect, and then reclassifying low-confidence pixels as necessary. Comparing the classification speeds of both algorithms to known baselines showed a slight speedup for large values of k (the number of clusters) for harvist-cluster, and a significant speedup for harvistSVM. Future work aims to automate the parameter tuning process required for harvistSVM, and further improve classification accuracy and speed. Additionally, this research will move documents created in Canvas into ArcGIS. The launch of the Mars Reconnaissance Orbiter (MRO) will provide a wealth of image data such as global maps of Martian weather and high resolution global images of Mars. The ability to store this new data in a georeferenced format will support future Mars missions by providing data for landing site selection and the search for water on Mars.

Kocurek, Michael J.↗
NASA NTRSDate not supplied

Latest Progress and Results in LEO-GEO and GEO-GEO Stereo AMVs

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectro–radiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, offering a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

Atmospheric motion vectors↗
NASA NTRS1998

A Novel Sensor for Attitude Determination Using Global Positioning System Signals

An entirely new sensor approach for attitude determination using Global Positioning System (GPS) signals is developed. The concept involves the use of multiple GPS antenna elements arrayed on a single sensor head to provide maximum GPS space vehicle availability. A number of sensor element configurations are discussed. In addition to the navigation function, the array is used to find which GPS space vehicles are within the field-of-view of each antenna element. Attitude determination is performed by considering the sightline vectors of the found GPS space vehicles together with the fixed boresight vectors of the individual antenna elements. This approach has clear advantages over the standard differential carrier-phase approach. First, errors induced by multipath effects can be significantly reduced or eliminated altogether. Also, integer ambiguity resolution is not required, nor do line biases need to be determined through costly and cumbersome self-surveys. Furthermore, the new sensor does not require individual antennas to be physically separated to form interferometric baselines to determine attitude. Finally, development potential of the new sensor is limited only by antenna and receiver technology development unlike the physical limitations of the current interferometric attitude determination scheme. Simulation results indicate that accuracies of about 1 degree (3 omega) are possible.

Crassidis, John L.↗
NASA NTRS2014

Space Launch System Development Status

Development of NASA's Space Launch System (SLS) heavy lift rocket is shifting from the formulation phase into the implementation phase in 2014, a little more than three years after formal program approval. Current development is focused on delivering a vehicle capable of launching 70 metric tons (t) into low Earth orbit. This "Block 1" configuration will launch the Orion Multi-Purpose Crew Vehicle (MPCV) on its first autonomous flight beyond the Moon and back in December 2017, followed by its first crewed flight in 2021. SLS can evolve to a130-t lift capability and serve as a baseline for numerous robotic and human missions ranging from a Mars sample return to delivering the first astronauts to explore another planet. Benefits associated with its unprecedented mass and volume include reduced trip times and simplified payload design. Every SLS element achieved significant, tangible progress over the past year. Among the Program's many accomplishments are: manufacture of Core Stage test panels; testing of Solid Rocket Booster development hardware including thrust vector controls and avionics; planning for testing the RS-25 Core Stage engine; and more than 4,000 wind tunnel runs to refine vehicle configuration, trajectory, and guidance. The Program shipped its first flight hardware - the Multi-Purpose Crew Vehicle Stage Adapter (MSA) - to the United Launch Alliance for integration with the Delta IV heavy rocket that will launch an Orion test article in 2014 from NASA's Kennedy Space Center. Objectives of this Earth-orbit flight include validating the performance of Orion's heat shield and the MSA design, which will be manufactured again for SLS missions to deep space. The Program successfully completed Preliminary Design Review in 2013 and Key Decision Point C in early 2014. NASA has authorized the Program to move forward to Critical Design Review, scheduled for 2015 and a December 2017 first launch. The Program's success to date is due to prudent use of proven technology, infrastructure, and workforce from the Saturn and Space Shuttle programs, a streamlined management approach, and judicious use of new technologies. The result is a safe, affordable, sustainable, and evolutionary path to development of an unprecedented capability for future missions across the solar system. In an environment of economic challenges, the nationwide SLS team continues to meet ambitious budget and schedule targets. This paper will discuss SLS program and technical accomplishments over the past year and provide a look at the milestones and challenges ahead.

Lyles, Garry↗
NASA NTRS2014

NASA's Space Launch System Development Status

Development of the National Aeronautics and Space Administration's (NASA's) Space Launch System (SLS) heavy lift rocket is shifting from the formulation phase into the implementation phase in 2014, a little more than 3 years after formal program establishment. Current development is focused on delivering a vehicle capable of launching 70 metric tons (t) into low Earth orbit. This "Block 1" configuration will launch the Orion Multi-Purpose Crew Vehicle (MPCV) on its first autonomous flight beyond the Moon and back in December 2017, followed by its first crewed flight in 2021. SLS can evolve to a130t lift capability and serve as a baseline for numerous robotic and human missions ranging from a Mars sample return to delivering the first astronauts to explore another planet. Benefits associated with its unprecedented mass and volume include reduced trip times and simplified payload design. Every SLS element achieved significant, tangible progress over the past year. Among the Program's many accomplishments are: manufacture of core stage test barrels and domes; testing of Solid Rocket Booster development hardware including thrust vector controls and avionics; planning for RS- 25 core stage engine testing; and more than 4,000 wind tunnel runs to refine vehicle configuration, trajectory, and guidance. The Program shipped its first flight hardware - the Multi-Purpose Crew Vehicle Stage Adapter (MSA) - to the United Launch Alliance for integration with the Delta IV heavy rocket that will launch an Orion test article in 2014 from NASA's Kennedy Space Center. The Program successfully completed Preliminary Design Review in 2013 and will complete Key Decision Point C in 2014. NASA has authorized the Program to move forward to Critical Design Review, scheduled for 2015 and a December 2017 first launch. The Program's success to date is due to prudent use of proven technology, infrastructure, and workforce from the Saturn and Space Shuttle programs, a streamlined management approach, and judicious use of new technologies. The result is a safe, affordable, sustainable, and evolutionary path to development of an unprecedented capability for future missions across the solar system. In an environment of economic challenges, the nationwide SLS team continues to meet ambitious budget and schedule targets. This paper will discuss SLS Program and technical accomplishments over the past year and provide a look at the milestones and challenges ahead.

Lyles, Garry↗
NASA NTRS1994

High-angle-of-attack yawing moment asymmetry of the X-31 aircraft from flight test

Significant yawing moment asymmetries were encountered during the high-angle-of-attack envelope expansion of the two X-31 aircraft. These asymmetries led to position saturations of the thrust vector vanes and trailing-edge flaps during some of the dynamic stability axis rolling maneuvers at high angles of attack. This slowed the high-angle-of-attack envelope expansion and resulted in maneuver restrictions. Several aerodynamic modifications were made to the X-31 forebody with the goal of minimizing the asymmetry. A method for determining the yawing moment asymmetry from flight data was developed and an analysis of the various configuration changes completed. The baseline aircraft were found to have significant asymmetries above 45 deg angle of attack with the largest asymmetry typically occurring around 60 deg angle of attack. Applying symmetrical boundary layer transition strips along the forebody sides increased the magnitude of the asymmetry and widened the angle-of-attack range over which the largest asymmetry acted. Installing longitudinal forebody strakes and rounding the sharp nose of the aircraft caused the yawing moment asymmetry magnitude to be reduced. The transition strips and strakes made the asymmetry characteristic of the aircraft more repeatable than the clean forebody configuration. Although no geometric differences between the aircraft were known, ship 2 consistently had larger yawing moment asymmetries than ship 1.

Cobleigh, Brent R.↗
DOE OSTI2024

Bridging the Gap Between LLMs and LNS with Dynamic Data Format and Architecture Codesign

Deep neural networks (DNNs) have achieved tremendous success in the past few years. However, their training and inference demand exceptional computational and memory resources. Quantization has been shown as an effective approach to mitigate the cost, with the mainstream data types reduced from FP32 to FP16/BF16 and recently FP8 in the latest NVIDIA H100 GPUs. With increasingly aggressive quantization, however, the conventional floating-point formats suffer from limited precision in representing numbers around zero. Recently, NVIDIA demonstrated the potential of using a Logarithmic Number System (LNS) for the next generation of tensor cores. While LNS mitigates the hurdles in representing small numbers, in this work we observed a mismatch between LNS and the emerging Large Language Models (LLM), where LLM exhibits significant outliers when directly adopting the LNS format. In this paper, we present a data-format/architecture codesign to bright this gap. On the format side, we propose a dynamic LNS format to flexibly represent outliers at a higher precision, by exploiting asymmetry in the LNS representation and identifying outliers through a per-vector basis. On the architecture side, for demonstration, we realize the dynamic LNS format in a systolic array, which can handle the irregularity of the outliers at runtime. We implement our approach on an Alveo U280 FPGA as a prototype. Experimental results show that our design can effectively handle the outliers and resolve the mismatch between LNS and LLM, contributing to an accuracy improvement of 15.4% and 16% over the floating-point and the original LNS baselines, using four state-of-the-art LLM models. Our observation and design lay a solid foundation for the large-scale adoption of the LNS format in the next-generation deep learning hardware.

Haghi, Pouya↗
DOE OSTI2020

First Principles Nonadiabatic Excited-State Molecular Dynamics in NWChem

Computational simulation of non-adiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons, to name a few. Here, we report an implementation of the fewest-switches surface hopping algorithm in the NWChem computational chemistry program. Here the surface hopping method is combined with linear-response time-dependent density functional theory calculations of adiabatic excited state potential energy surfaces. To treat quantum transitions between arbitrary electronic Born{Oppenheimer states, we have implemented both numerical and analytical differentiation schemes for derivative non-adiabatic couplings. A numerical approach for the time-derivative non-adiabatic couplings together with an analytical method for calculating non-adiabatic coupling vectors is an efficient combination for surface hopping approaches. Additionally, electronic decoherence schemes and a state reassigned unavoided crossings algorithm are also implemented to improve the accuracy of the simulated dynamics and to handle trivial unavoided crossings. We apply our code to study the ultrafast decay of photoexcited benzene, including a detailed analysis of the potential energy surface, population decay time scales, and vibrational coordinates coupled to the excitation dynamics. The development presented in this work is a baseline for future implementations of more sophisticated frameworks for simulating of non-adiabatic molecular dynamics in NWChem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Discriminating Accretion States via Rotational Symmetry in Simulated Polarimetric Images of M87

In 2017 April, the Event Horizon Telescope observed the shadow of the supermassive black hole at the core of the elliptical galaxy Messier 87. While the original image was constructed from measurements of the total intensity, full polarimetric data were also collected, and linear polarimetric images are expected in the near future. We propose a modal image decomposition of the linear polarization field into basis functions with varying azimuthal dependence of the electric vector position angle. We apply this decomposition to images of ray traced general relativistic magnetohydrodynamics simulations of the Messier 87 accretion disk. Furthermore, for simulated images that are physically consistent with previous observations, the magnitude of the coefficient associated with rotational symmetry, β2, is a useful discriminator between accretion states. We find that at 20 μas resolution, $| {\beta }_{2}| $ is greater than 0.2 only for models of disks with horizon-scale magnetic pressures large enough to disrupt steady accretion. We also find that images with a more radially directed electric vector position angle correspond to models with higher black hole spin. Our analysis demonstrates the utility of the proposed decomposition as a diagnostic framework to improve constraints on theoretical models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Solar neutrinos and the strongest oscillation constraints on scalar NSI

Scalar non-standard neutrino interactions (sNSI) is a scenario where neutrinos can develop a medium dependent contribution to their mass due to a new scalar mediator. This scenario differs from the commonly discussed vector mediator case in that the oscillation effect scales with density rather than density and neutrino energy. Thus the strongest oscillation constraint comes from solar neutrinos which experience the largest density in a neutrino oscillation experiment. We derive constraints on all the sNSI parameters as well as the absolute neutrino mass scale by combining solar and reactor data and find solar neutrinos to be > 1 order of magnitude more sensitive to sNSI than terrestrial probes such as long-baseline experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

Plate tectonics from VLBI and SLR global data

This study is based on data derived from fifteen years of observations of the SLR (side-looking radar) network and six years of the VLBI (very long baseline interferometry) network. In order to use all available information VLBI and SLR global data sets were combined in a least squares fashion to calculate station horizontal velocities. All significant data pertaining to a single site contribute to the station horizontal motion. The only constraint on the solution is that no vertical motion is allowed. This restriction does not greatly affect the precision of the overall solution given the fact that the expected vertical motion for most stations, even those experiencing post glacial uplift, is well under 1 cm/yr. Since the average baseline is under 4,000 km, only a small fraction of the station vertical velocity is translated into baseline rates so that the error introduced in the solution by restricting up-down station movement is minimal. As a reference, station velocities were then compared to the ones predicted by the NUVEL-1 geological model of DeMets et al. (1990). The focus of the study is on analyzing these discrepancies for global plate tectonics as well as regional tectonic settings. The method used also allows us not only to derive horizontal motion for individual stations but also to calculate Euler vectors for those plates that have enough stations located on the stable interior like North America, Pacific, Eurasia, and Australia.

Harrison, Christopher G. A.↗
NASA NTRS1991

Candidate control design metrics for an agile fighter

Success in the fighter combat environment of the future will certainly demand increasing capability from aircraft technology. These advanced capabilities in the form of superagility and supermaneuverability will require special design techniques which translate advanced air combat maneuvering requirements into design criteria. Control design metrics can provide some of these techniques for the control designer. Thus study presents an overview of control design metrics and investigates metrics for advanced fighter agility. The objectives of various metric users, such as airframe designers and pilots, are differentiated from the objectives of the control designer. Using an advanced fighter model, metric values are documented over a portion of the flight envelope through piloted simulation. These metric values provide a baseline against which future control system improvements can be compared and against which a control design methodology can be developed. Agility is measured for axial, pitch, and roll axes. Axial metrics highlight acceleration and deceleration capabilities under different flight loads and include specific excess power measurements to characterize energy meneuverability. Pitch metrics cover both body-axis and wind-axis pitch rates and accelerations. Included in pitch metrics are nose pointing metrics which highlight displacement capability between the nose and the velocity vector. Roll metrics (or torsion metrics) focus on rotational capability about the wind axis.

Murphy, Patrick C.↗
DOE OSTI2023

Ground Vehicle Generalized Forces and Moment Governor Design Via Noncertainty-Equivalent Adaptive Prescribed Performance Control

Torque-vectoring technology demonstrates great potential in improving the safety and performance of ground vehicles. In this paper, a novel generalized forces and moment governor for torque vectoring is suggested. The proposed solution strategically combines prescribed performance control, noncertainty equivalent adaptive control design, and a smooth projection operator. The main advantage of the proposed control strategy lies in its capability to guarantee both the transient performance and prompt recovery of the desired deterministic behavior of the closed-loop adaptive system, even in the presence of parametric uncertainties. ASM simulation results are presented to validate the efficacy of the proposed generalized forces and moment governor and to demonstrate its superiority over a baseline solution.

Zhou, Xingyu↗
DOE OSTI2022

Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network.

Neural operators have recently become popular tools for designing solution maps between function spaces in the form of neural networks. Differently from classical scientific machine learning approaches that learn parameters of a known partial differential equation (PDE) for a single instance of the input parameters at a fixed resolution, neural operators approximate the solution map of a family of PDEs [6, 7]. Despite their success, the uses of neural operators are so far restricted to relatively shallow neural networks and confined to learning hidden governing laws. In this work, we propose a novel nonlocal neural operator, which we refer to as nonlocal kernel network (NKN), that is resolution independent, characterized by deep neural networks, and capable of handling a variety of tasks such as learning governing equations and classifying images. Our NKN stems from the interpretation of the neural network as a discrete nonlocal diffusion reaction equation that, in the limit of infinite layers, is equivalent to a parabolic nonlocal equation, whose stability is analyzed via nonlocal vector calculus. The resemblance with integral forms of neural operators allows NKNs to capture long-range dependencies in the feature space, while the continuous treatment of node-to-node interactions makes NKNs resolution independent. The resemblance with neural ODEs, reinterpreted in a nonlocal sense, and the stable network dynamics between layers allow for generalization of NKN’s optimal parameters from shallow to deep networks. This fact enables the use of shallow-to-deep initialization techniques [8]. Our tests show that NKNs outperform baseline methods in both learning governing equations and image classification tasks and generalize well to different resolutions and depths.

97 MATHEMATICS AND COMPUTING↗